Understanding norovirus reporting patterns in England: a mixed model approach

Abstract

Background: Norovirus has a higher level of under-reporting in England compared to other intestinal infectious agents such as Campylobacter or Salmonella, despite being recognised as the most common cause of gastroenteritis globally. In England, this under-reporting is a consequence of the frequently mild/self-limiting nature of the disease, combined with the passive surveillance system for infectious diseases reporting. We investigated heterogeneity in passive surveillance system in order to improve understanding of differences in reporting and laboratory testing practices of norovirus in England.

Methods: The reporting patterns of norovirus relating to age and geographical region of England were investigated using a multivariate negative binomial model. Multiple model formulations were compared, and the best performing model was determined by proper scoring rules based on one-week-ahead predictions. The reporting patterns are represented by epidemic and endemic random intercepts; values close to one and less than one imply a lower number of reports than expected in the given region and age-group.

Results: The best performing model highlighted atypically large and small amounts of reporting by comparison with the average in England. Endemic random intercept varied from the lowest in East Midlands in those in the under 5 year age-group (0.36, CI 0.18-0.72) to the highest in the same age group in South West (3.00, CI 1.68-5.35) and Yorkshire & the Humber (2.93, CI 1.74-4.94). Reporting by age groups showed the highest variability in young children.

Conclusion: We identified substantial variability in reporting patterns of norovirus by age and by region of England. Our findings highlight the importance of considering uncertainty in the design of forecasting tools for norovirus, and to inform the development of more targeted risk management approaches for norovirus disease.

Keywords: HHH4; Mixed-effects; Negative binomial; Norovirus; Public health surveillance; Underestimation.

Fig. 1

Regional model fit and the relative contribution of model components. Epidemic (within + between) and endemic components per region, aggregated over age groups from the best performing model (B2). The dots represent the actual reported norovirus cases

Fig. 2

Age-group-based model fit and the relative contribution of model components. Epidemic (within + between) and endemic components per age group, aggregated over regions from the best performing model (B2). The dots represent the actual reported norovirus cases

Fig. 3

Age group- and region-specific endemic random intercepts. RI < 1 suggests lower number of norovirus reports than expected. The Nomenclature of Territorial Units for Statistics (NUTS) Level 1 codes can be mapped to regional names as follows: UKC - North East, UKD – North West, UKE – Yorkshire & Humber, UKF – East Midlands, UKG – West Midlands, UKH – East of England, UKI – London, UKJ – South East, UKK – South West